SciML/NeuralPDE.jl
Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
JuliaNOASSERTION
Stargazers
- acganeshSan Francisco, CA
- agdollaBudapest, Hungary
- akayshAmherst
- alec-hoyland@YurtsAI
- anandijainSan Jose CA, Boston MA
- AStupidBear
- atgmello@grupo-xp
- ayush-1506SF Bay Area
- BingHanLinTaiwan, Taichung
- cal-miller-harvardUniversity of Colorado, Boulder
- chriscoey@RelationalAI
- cmcaineLeeds Institute for Data Analytics, University of Leeds
- edwinksl@bazantgroup
- emerali@PIQuIL
- JucksonP
- knizkarBratislava, Slovakia
- liuyxppFudan University
- m-pedroAI, Machine Learning, AGI
- matthieugomezColumbia University
- MaximilianJHuberNYU Econ
- miguelrazUNAM
- mindboundD8 Corporation
- OO0OOO00O0OOO0O00OOO0OO
- perrutquistIMTEK, University of Freiburg
- ptigasUniversity of Oxford
- QPIpattern
- shipengcheng1230Capital One
- ShreyasFadnavis@harvard @nipy @dipy
- sonamghoshSan Francisco, CA
- SuXY15Beijing
- tejank10Avataar.ai
- tlienartEU
- ujjwal-9@qureai
- vicmohUniversity of Guelph
- waipotn
- WuShichaoMax Planck Institute for Gravitational Physics